"""GPU编码器实现"""

import asyncio
from typing import Optional, Dict, Any
from pathlib import Path

from ..scheduler.task import TranscodeTask


class GpuEncoder:
    """GPU编码器基类"""
    
    def __init__(self, gpu_type: str):
        self.gpu_type = gpu_type
        self.initialized = False
        self.encoder = None
    
    async def initialize(self) -> bool:
        """初始化编码器"""
        try:
            # 根据GPU类型初始化不同的编码器
            if self.gpu_type == "nvidia":
                await self._init_nvidia_encoder()
            elif self.gpu_type == "amd":
                await self._init_amd_encoder()
            elif self.gpu_type == "intel":
                await self._init_intel_encoder()
            else:
                # 自动检测
                await self._init_auto_encoder()
            
            self.initialized = True
            return True
            
        except Exception as e:
            print(f"GPU编码器初始化失败: {e}")
            return False
    
    async def _init_nvidia_encoder(self) -> None:
        """初始化NVIDIA编码器"""
        # 使用NVIDIA硬件编码器
        # 这里需要集成NVIDIA Video Codec SDK
        pass
    
    async def _init_amd_encoder(self) -> None:
        """初始化AMD编码器"""
        # 使用AMD硬件编码器
        # 这里需要集成AMD AMF SDK
        pass
    
    async def _init_intel_encoder(self) -> None:
        """初始化Intel编码器"""
        # 使用Intel硬件编码器
        # 这里需要集成Intel Media SDK
        pass
    
    async def _init_auto_encoder(self) -> None:
        """自动检测并初始化编码器"""
        # 尝试按优先级初始化编码器
        encoders = ["nvidia", "amd", "intel"]
        
        for encoder_type in encoders:
            try:
                if encoder_type == "nvidia":
                    await self._init_nvidia_encoder()
                    self.gpu_type = "nvidia"
                    break
                elif encoder_type == "amd":
                    await self._init_amd_encoder()
                    self.gpu_type = "amd"
                    break
                elif encoder_type == "intel":
                    await self._init_intel_encoder()
                    self.gpu_type = "intel"
                    break
            except Exception:
                continue
        else:
            raise RuntimeError("未找到可用的GPU编码器")
    
    async def encode_task(self, task: TranscodeTask) -> bool:
        """执行转码任务"""
        if not self.initialized:
            raise RuntimeError("编码器未初始化")
        
        try:
            task.start()
            
            # 使用PyAV进行硬件加速编码
            import av
            
            # 打开输入文件
            input_container = av.open(str(task.input_path))
            
            # 创建输出文件
            output_container = av.open(str(task.output_path), mode='w')
            
            # 配置输出流
            input_stream = input_container.streams.video[0]
            output_stream = output_container.add_stream(
                codec_name=self._get_codec_name(),
                rate=input_stream.average_rate,
                options=self._get_encoder_options()
            )
            
            # 转码处理
            frame_count = 0
            total_frames = input_stream.frames if input_stream.frames else 0
            
            for frame in input_container.decode(video=0):
                if task.status != task.status.RUNNING:
                    break
                
                # 处理帧
                processed_frame = self._process_frame(frame)
                
                # 编码帧
                for packet in output_stream.encode(processed_frame):
                    output_container.mux(packet)
                
                frame_count += 1
                
                # 更新进度
                if total_frames > 0:
                    progress = (frame_count / total_frames) * 100
                    fps = 1.0  # 这里需要实际计算FPS
                    task.update_progress(progress, fps)
                
                # 异步等待，避免阻塞
                await asyncio.sleep(0)
            
            # 刷新编码器
            for packet in output_stream.encode():
                output_container.mux(packet)
            
            # 关闭文件
            input_container.close()
            output_container.close()
            
            task.complete()
            return True
            
        except Exception as e:
            task.fail(str(e))
            return False
    
    def _get_codec_name(self) -> str:
        """获取编码器名称"""
        codec_map = {
            "nvidia": "h264_nvenc",
            "amd": "h264_amf",
            "intel": "h264_qsv",
        }
        return codec_map.get(self.gpu_type, "libx264")
    
    def _get_encoder_options(self) -> Dict[str, Any]:
        """获取编码器选项"""
        options = {
            "preset": "medium",
            "crf": "23",
        }
        
        if self.gpu_type == "nvidia":
            options.update({
                "preset": "p4",
                "tune": "hq",
            })
        elif self.gpu_type == "amd":
            options.update({
                "quality": "speed",
            })
        elif self.gpu_type == "intel":
            options.update({
                "preset": "medium",
            })
        
        return options
    
    def _process_frame(self, frame) -> Any:
        """处理视频帧"""
        # 这里可以添加帧处理逻辑，如滤镜、缩放等
        return frame
    
    async def cleanup(self) -> None:
        """清理资源"""
        if self.encoder:
            # 清理编码器资源
            pass
        self.initialized = False


class EncoderManager:
    """编码器管理器"""
    
    def __init__(self):
        self.encoders: Dict[str, GpuEncoder] = {}
        self.available_gpus: List[Dict[str, Any]] = []
    
    async def initialize(self) -> bool:
        """初始化编码器管理器"""
        try:
            # 检测可用GPU
            await self._detect_gpus()
            
            # 为每个GPU创建编码器
            for gpu_info in self.available_gpus:
                encoder = GpuEncoder(gpu_info["type"])
                if await encoder.initialize():
                    self.encoders[gpu_info["id"]] = encoder
            
            return len(self.encoders) > 0
            
        except Exception as e:
            print(f"编码器管理器初始化失败: {e}")
            return False
    
    async def _detect_gpus(self) -> None:
        """检测可用GPU"""
        self.available_gpus = []
        
        try:
            # 检测NVIDIA GPU
            import GPUtil
            nvidia_gpus = GPUtil.getGPUs()
            for gpu in nvidia_gpus:
                self.available_gpus.append({
                    "type": "nvidia",
                    "id": f"nvidia_{gpu.id}",
                    "name": gpu.name,
                    "memory": gpu.memoryTotal,
                })
        except ImportError:
            pass
        
        # 这里可以添加AMD和Intel GPU的检测逻辑
    
    async def get_encoder(self, gpu_id: Optional[str] = None) -> Optional[GpuEncoder]:
        """获取编码器"""
        if not self.encoders:
            return None
        
        if gpu_id and gpu_id in self.encoders:
            return self.encoders[gpu_id]
        
        # 返回第一个可用的编码器
        return next(iter(self.encoders.values()), None)
    
    async def encode_task(self, task: TranscodeTask) -> bool:
        """执行转码任务"""
        encoder = await self.get_encoder(task.gpu_type)
        if not encoder:
            task.fail("未找到可用的编码器")
            return False
        
        return await encoder.encode_task(task)
    
    async def cleanup(self) -> None:
        """清理所有编码器"""
        for encoder in self.encoders.values():
            await encoder.cleanup()
        self.encoders.clear()